A variety of industrial as well as non-industrial applications use fuel burning boilers, typically for converting chemical energy into thermal energy by burning one of various types of fuels, such as coal, gas, oil, waste material, etc. An exemplary use of fuel burning boilers is in thermal power generators, wherein fuel burning boilers are used to generate steam from water traveling through a number of pipes and tubes in the boiler and the steam is then used to generate electricity in one or more turbines. The output of a thermal power generator is a function of the amount of heat generated in a boiler, wherein the amount of heat is determined by the amount of fuel that can be burned per hour, etc. Additionally, the output of the thermal power generator may also be dependent upon the heat transfer efficiency of the boiler used to burn the fuel.
Burning of certain types of fuel, such as coal, oil, waste material, etc., generates a substantial amount of soot, slag, ash and other deposits (generally referred to as “soot”) on various surfaces in the boilers, including the inner walls of the boiler as well as on the exterior walls of the tubes carrying water through the boiler. The soot deposited in the boiler has various deleterious effects on the rate of heat transferred from the boiler to the water, and thus on the efficiency of any system using such boilers. It is necessary to address the problem of soot in fuel burning boilers that burn coal, oil, and other such fuels that generate soot in order to maintain a desired efficiency within the boiler. While not all fuel burning boilers generate soot, for the remainder of this patent, the term “fuel burning boilers” is used to refer to those boilers that generate soot.
Various solutions have been developed to address the problems caused by the generation and presence of soot deposits in boilers of fuel burning boilers. One approach is the use of soot blowers to remove soot encrustations accumulated on boiler surfaces through the creation of mechanical and thermal shock. Another approach is to use various types of soot blowers to spray cleaning materials through nozzles, which are located on the gas side of the boiler walls and/or on other heat exchange surfaces, where such soot blowers use any of the various media such as saturated steam, superheated steam, compressed air, water, etc., for removing soot from the boilers.
Soot blowing affects the efficiency and the expense of operating a fuel burning boiler. For example, if inadequate soot blowing is applied in a boiler, it results in excessive soot deposits on the surfaces of various steam carrying pipes and therefore in lower heat transfer rates. In some cases, inadequate soot blowing may result in “permanent fouling” within fuel burning boilers, meaning that soot deposits in the boiler are so excessive that such deposits cannot be removed by any additional soot blowing. In such a case, forced outage of the boiler operation may be required to fix the problem of excessive soot deposits, and boiler maintenance personnel may have to manually remove the soot deposits using hammers and chisels. Such forced outages are not only expensive, but also disruptive for the systems using such fuel burning boilers.
On the other hand, excessive soot blowing in fuel burning boilers may result in increased energy cost to operate the soot blowers, wastage of steam that could otherwise be used to operate turbines, etc. Excessive soot blowing may also be linked to boiler wall tube thinning, tube leaks, etc., which may cause forced outages of boiler use. Therefore, the soot blowing process needs to be carefully controlled.
Historically, soot blowing in utility boilers has been mostly an ad hoc practice, generally relying on a boiler operator's judgment. Such an ad hoc approach produces very inconsistent results. Therefore, it is important to manage the process of soot blowing more effectively and in a manner so that the efficiency of boiler operations is maximized and the cost associated with the soot blowing operations is minimized. One measure that has been used in soot blowing control is the cleanliness of the boiler or heat exchanger. The cleanliness may be expressed in terms of a cleanliness factor CF that is a measure of how close the actual operating conditions of the boiler or heat exchanger are to the ideal operating conditions. In some control methods, the heat absorption of the boiler or heat exchanger serves as the basis for determining the cleanliness, with CF=Qactual/Qideal, where Qactual is the current actual heat absorption and Qideal is the achievable ideal heat absorption after cleaning. Of course, other relevant parameters that vary as the cleanliness of the boiler or heat exchanger varies may be used to calculate a cleanliness factor. When the boiler or heat exchanger is operating near the optimal efficiency, Qactual approaches Qideal and CF≈1. As CF varies during operation, the soot blowing operation is adjusted to increase heat absorption to a desired level by the boiler operators.
One popular method used for determining cleanliness of a boiler section and to control soot blowing operations is a first principle based method, which requires measurements of flue gas temperature and steam temperature at the boiler section inlets and outlets. However, because direct measurements of flue gas temperatures are not always available, the flue gas temperatures are often backward calculated at multiple points along the path of the flue gas, starting from the known flue gas temperatures measured at an air heater outlet. This method is quite sensitive to disturbances and variations in air heater outlet flue gas temperatures and fuel changes, often resulting in incorrect results. Moreover, this method is a steady state method, and therefore does not work well in transient processes generally encountered in various boiler sections.
Another popular method used for determining cleanliness of a boiler section of a fuel burning boiler and to control soot blowing operations in a fuel burning boiler is an empirical model based method, which relies on an empirical model such as a neural network model, a polynomial fit model, etc. The empirical model based method generally requires a large quantity of empirical data related to a number of parameters, such as the fuel flow rate, the air flow rate, the air temperature, the water/steam temperature, the burner tilt, etc. Unfortunately the large amount of data makes the data collection process tedious and prone to high amount of errors in data collection.
Another method used to control soot blowing operations in a fuel burning boiler is disclosed in U.S. Patent Publ. No. 2006/0283406 A1, by Francino et al., published on Dec. 21, 2006, entitled “Method and Apparatus for Controlling Soot Blowing Using Statistical Process Control,” the disclosure of which is expressly incorporated herein. Francino et al. discloses a statistical process control system employing a consistent soot blowing operation for a heat exchange section of, for example, a fuel burning boiler, collecting heat absorption data for the heat exchange section and analyzing the distribution of the heat absorption data as well as various parameters of the heat absorption distribution to readjust the soot blowing operation. The statistical process control system may set a desired lower heat absorption limit and a desired upper heat absorption limit and compare them, respectively, with an actual lower heat absorption limit and an actual upper heat absorption limit to determine the readjustment to be made to the soot blowing practice.
Generally speaking, the statistical process control system is simple to implement as the statistical process control system requires only heat absorption data for implementation. Moreover, because the statistical process control system uses heat absorption data, it is independent of, and not generally effected by disturbances and noise in flue gas temperatures, thus providing uniform control over operation of soot blowers and cleanliness of heat exchange sections. An implementation of the statistical process control system measures heat absorption at various points over time to determine differences in heat absorption before and after a soot blowing operation, and calculates various statistical process control measurements based on such heat absorption statistics to determine the effectiveness of the soot blowing operation. The statistical process control system establishes a consistent soot blowing operation for the heat exchange section of a boiler or other machines and reduces the amount of data necessary for controlling the operation of the soot blowers.
In these and other intelligent soot blowing methods, the actual operating conditions of the boiler or boiler section are compared to the ideally clean conditions to control the sequence, timing and duration of actuation of the various soot blowers of the section. The comparison is also used to determine when the permanent soot buildup in the section is so great that the boiler must be shut down for cleaning. In the soot blowing methods, data relating to the operation of a boiler section is collected at the boiler section over a period of time, and the performance of the boiler section is modeled to express a relevant thermodynamic parameter as a function of the other measured thermodynamic parameters. For example, in some implementations, the heat absorption Q of the boiler section is modeled as a function of the steam flow rate Fs, the steam temperature at the inlet Tsi and the flue gas temperature at the inlet Tgi. Of course, the particular method may be configured to model other meaningful parameters of the boiler section.
Regardless of the modeled parameter, the intelligent soot blowing methods typically use only one ideal model or benchmark per section to which the current conditions within the boiler section are compared. Soot blowing can be properly controlled using a single model if the generated model provides an accurate depiction of the operation of the boiler section. However, if the generated model is not accurate, the control of the soot blowing operation may cause the operation and, consequently, the boiler section to operate with less efficiency than can be attained with an accurate model. Inaccuracies in the model may be caused by many factors, such as the inability to directly measure certain parameters that are meaningful to the modeling of the boiler section, sensitivity within a given method to disturbances and variations in parameters, the completeness and accuracy of the data provided to the modeling software, and the like. Because only a single model or benchmark is used, it is often difficult to determine whether the generated model is accurate and reliable for the purposes of controlling the soot blowing operation. As a result, a need exists for an improved method of controlling the soot blowing operation of the boiler sections that facilitates the identification of inaccuracies and unreliability of the generated models so that the models may be adjusted or recalculated if necessary to ensure that the soot blowing operation is being performed as efficiently as possible.